Senior AI Reliability Engineer (Platform)
Tasks
- Assess hallucination risk and retrieval quality
- Build automated testing pipelines
- Define and monitor quality reliability safety metrics
- Design build evaluation frameworks
- Develop SLOs SLIs monitoring alerting
- Guide build versus buy model selection decisions
- Implement observability and drift detection
- Implement permissions auditability human oversight
- Manage incident response runbooks root cause analysis
- Orchestrate multi agent governance and guardrails
- Participate in on-call rotations
- Partner to evaluate AI solutions and standards
- Support experimentation for emerging AI technologies
- Support secure deployment patterns for AI systems
Perks/Benefits
Skills/Tech-stack
AWS | Adversarial Testing | Agent systems | Agentic Workflows | Airflow | Alerting | Automated testing | CI/CD | Cause analysis | Containers | DBT | Data Pipelines | Databricks | Datadog | Drift Detection | Evaluation Frameworks | GitLab CI | GitLab CI/CD | Incident Response | Kubernetes | LLM | Logging | MLOps | Machine Learning | Monitoring | Multi-Agent | Multi-Agent Systems | Observability | OpenTelemetry | Prompt engineering | Python | RAG | Ray | Red Teaming | Root Cause Analysis | Root cause | SLI | SLO | SSE | SageMaker | Secure deployment | Spark | Splunk | Statistical Analysis | Tracing | Uncertainty Estimation | Version control | Workflow Orchestration
Education
N/A
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